DataHour: Building and Operationalizing an Explainable Predictive Model
DataHour: Building and Operationalizing an Explainable Predictive Model
12 Jan 202315:01pm - 12 Jan 202316:01pm
DataHour: Building and Operationalizing an Explainable Predictive Model
About the Event
One of the main barriers in making decisions based on machine learning models is the lack of transparency. Basically, users and decision makers need to know how these models derive their conclusion and understand the underlying reasons. Addressing these questions is the essence of “explainability,” and getting it right is becoming essential.
During this session we will use a real-world use case to build a predictive model and then add the explainable AI at top of it to make the model transparent and interpretable for business users.
In this DataHour, Amir will explain how to use Python packages OmniAXI as a model agnostic explainable AI. He will also cover how Streamlit and Flask deploy and operationalize both predictive and explanation models.
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
Who is this DataHour for?
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
- Best articles get published on Analytics Vidhya’s Blog Space
About the Speaker
Participate in discussion
Registration Details
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